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* feat(screener): 选股引擎支持 ETF - 12 个内置策略打 asset_types 白名单 + strategy_supports_asset;涨停类 (连板/断板反包)仅股票,其余 10 个技术类对 ETF 开放 - ScreenerService(repo, asset_type) 分流取数,ETF 复用 kline_etf_enriched, 跳过股票专用历史缓存与涨停信号;进程级 _history_cache key 含 asset_type - API /run、/run_preset 透传 asset_type;/strategies 按资产过滤; 股票专有策略在 ETF 下返回空 - 新增 enriched_dirname(asset_type) 共享 helper;get_enriched_latest_asset 增 refresh 参数(供轮询线程避免冷缓存同步重算) - 前端「策略」页加 股票/ETF 切换,ETF 走实时单跑(空日期→用 ETF 自身最新日); QK.screenerStrategies 按 asset_type keyed - 测试:test_screener_etf.py Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(backtest): 回测支持 ETF(个股/因子/策略组合) - 三条回测路径 + 共用 BacktestEngine 面板加载按 asset_type 路由到 kline_etf_enriched(复用 enriched_dirname);PanelCache key 隔离资产; ETF 跳过股票专用 get_enriched_range 缓存 - 面板 compute_all/名称 JOIN 按 asset_type 取维表(get_instruments_asset), 修复 ETF 策略回测用错股票维表致名称为空/涨停信号算错 - BacktestConfig/FactorConfig/StrategyBacktestConfig 增 asset_type - 三个回测 API + SSE stream 透传 asset_type;_make_job_key 纳入 asset_type (修复 stream 与 cancel job_key 不对齐致取消失效的回归) - 前端策略组合页/因子页加 股票/ETF 切换,标的搜索与策略列表跟随资产; assetType 持久化 - 测试:test_backtest_etf.py(含 job_key 一致性回归);既有回测测试替身同步 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(monitor): 监控规则支持 ETF - engine.evaluate(df, asset_type) 按规则 asset_type 分轮评估;quote_service 增开 ETF 评估轮(用 ETF enriched 快照),股票轮不受影响、不重置其策略结果 - ETF 评估轮独立 try(异常不丢弃已算出的股票告警)+ refresh=False(不在轮询 线程触发 ETF 冷缓存同步重算) - ETF 版历史加载器(main.py 注入)+ 按规则 asset_type 选加载器 - _strategy_pools 按 (sid, asset_type) 键,避免同策略股票/ETF 规则互相覆盖 - name_map 仅在有 ETF 规则时补 ETF 维表, setdefault 保股票名优先 - RuleModel/normalize 增 asset_type(默认 stock,持久化往返) - 前端 RuleEditor 加 股票/ETF 选择,策略列表与标的搜索跟随资产 - 测试:test_monitor_etf.py Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(etf): 前端 API 绑定透传 asset_type + 文档 - api.ts: screener/backtest 绑定加 assetType 参数,MonitorRule 类型加 asset_type - docs/features.md: 标注选股/回测/监控的 ETF 支持范围与前提 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(reliability): 管道并发/原子写/能力探测/监控告警多处加固 后端可靠性专项修复(均带回归测试, backend 全套 64 passed): 并发与数据完整性: - 盘后管道单飞: JobStore.create() 去重纳入 pending∨running, 关闭"两次快速点击" 并发双跑窗口; 新增 _heavy_run_lock 执行槽挡住 reap 后僵尸线程并发写 parquet - adj_factor/minute 全部改走原子写(tmp+replace), 消除 kill/断电致 all.parquet 损坏 - 分块拉取失败聚合 WARNING 可见化(不再静默当成功); 复权失败标的会保持旧价已提示 能力探测: - 周期重探(60min)热更新 app.state.capabilities, 付费 Key 过期/续费无需重启即可见 - 瞬时探测失败(超时/连接/5xx, 按 _is_transient 判定)不降级、保留旧付费档; 真 401/无权限仍正常降级回落 free-api 监控告警: - 评估仅在连续竞价(9:30-11:30/13:00-15:00)+ 快照当日新鲜度下进行, 避开集合竞价/ 收盘后陈旧价与节假日误告警 - scope=sector fail-closed(validate 拒绝新建 + _apply_scope 返回空), 修复板块规则 对全市场刷屏 - 飞书 webhook 加退避重试并移到独立线程池 fire-and-forget, 不再阻塞行情轮询线程 单标的新鲜度: 新增 repo.symbols_lagging() 检测掉队标的并 WARNING + 计入 job 结果 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
"""回归测试: 本轮修复的几处高风险行为(并发单飞 / 重任务槽 / sector fail-closed)。
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均为纯逻辑, 不触网, 不依赖真实数据源。
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"""
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from __future__ import annotations
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import polars as pl
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import pytest
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from app.services import pipeline_jobs
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from app.services.pipeline_jobs import JobStore
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from app.strategy import monitor_rules
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from app.strategy.monitor import MonitorRuleEngine
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# ── JobStore 单飞 ────────────────────────────────────────────────────────
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def test_create_singleflight_dedupes_pending_window(tmp_path):
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"""两次快速 create() 在 pending 窗口内应复用同一 job(is_new=False)。"""
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store = JobStore(store_dir=tmp_path / "jobs")
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jid1, new1 = store.create()
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assert new1 is True
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# 尚未 start(), job 仍是 pending —— 旧实现会在此另起新 job(并发双跑根因)
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jid2, new2 = store.create()
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assert jid2 == jid1
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assert new2 is False
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# start() 后仍复用同一活跃 job
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store.start(jid1)
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jid3, new3 = store.create()
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assert jid3 == jid1
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assert new3 is False
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def test_create_new_after_terminal(tmp_path):
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"""job 终态(succeed/fail)后, create() 应给出新 job。"""
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store = JobStore(store_dir=tmp_path / "jobs")
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jid1, _ = store.create()
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store.start(jid1)
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store.succeed(jid1, {"ok": True})
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jid2, new2 = store.create()
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assert jid2 != jid1
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assert new2 is True
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def test_run_slot_is_exclusive():
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"""重任务执行槽同一时刻只允许一个持有者(防僵尸并发)。"""
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assert pipeline_jobs.try_acquire_run_slot() is True
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try:
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# 已被占用, 第二次获取失败
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assert pipeline_jobs.try_acquire_run_slot() is False
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finally:
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pipeline_jobs.release_run_slot()
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# 释放后可再次获取
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assert pipeline_jobs.try_acquire_run_slot() is True
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pipeline_jobs.release_run_slot()
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# 重复释放幂等, 不抛
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pipeline_jobs.release_run_slot()
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# ── 监控 sector fail-closed ──────────────────────────────────────────────
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def _base_price_rule(scope: str) -> dict:
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return {
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"id": "r_test",
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"name": "t",
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"type": "price",
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"conditions": [{"field": "close", "op": ">", "value": 10}],
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"logic": "and",
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"scope": scope,
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}
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def test_validate_rejects_sector_scope():
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with pytest.raises(ValueError):
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monitor_rules.validate(_base_price_rule("sector"))
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def test_validate_accepts_symbols_scope():
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rule = _base_price_rule("symbols")
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rule["symbols"] = ["600000.SH"]
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monitor_rules.validate(rule) # 不应抛
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def test_apply_scope_sector_fails_closed():
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"""历史遗留 sector 规则在评估时应返回空(绝不退化为全市场)。"""
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df = pl.DataFrame({"symbol": ["600000.SH", "000001.SZ"], "close": [10.0, 20.0]})
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out = MonitorRuleEngine._apply_scope(df, {"id": "r_old", "scope": "sector"})
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assert out.is_empty()
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# 对照: scope=all 返回全量, symbols 过滤子集
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assert MonitorRuleEngine._apply_scope(df, {"scope": "all"}).height == 2
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picked = MonitorRuleEngine._apply_scope(
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df, {"scope": "symbols", "symbols": ["600000.SH"]}
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)
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assert picked.height == 1
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